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<Paper uid="P86-1005">
  <Title>Semantic Acquisition In TELI: A Transportable, User-Customized Natural Language Processor</Title>
  <Section position="2" start_page="0" end_page="20" type="intro">
    <SectionTitle>
1. Introduction
</SectionTitle>
    <Paragraph position="0"> In constructing the Transportable English-Language Interface system (TELI). we have sought to respond to problems of both an applied and a scientific nature. Concerning the applied side of computational linguistics, we seek to redress the fact that many natural language prototypes, despite their sophistication and even their robustness, have fallen into disuse because of failures (1) to make known to users exactly what inputs are allowed (e.g. what words and phrases are defined) and (2) to provide capabilities that meet the precise needs of a given user or group of users (e.g. appropriate vocabulary, syntax.</Paragraph>
    <Paragraph position="1"> and semantics). Since experience has shown that neither users nor svstem designers can predict in advance all the words, phrases, and associated meanings that will arise in accessing a given database (cf. Tennant. 1979). we have sought to make TELl &amp;quot;transportable&amp;quot; in an extreme sense, where customizations may be performed (1) by end users, as opposed to the system designers, and (2) at any time during the processing of English sentences, rather than requiring a complete customization before English processing may occur.</Paragraph>
    <Paragraph position="2"> In addition to the potential practical benefits of a user-customized interface, we feel that wellconceived transportability projects can make useful scientific contributions to computational linguistics since single-domain systems and, to a lesser extent, systems adapted over weeks or months by their designers, afford opportunities to circumvent, rather than squarely address, important issues concerning (a) the precise nature of the formalisms the system is designed around, and (b) the interactions among system modules. Although customization efforts offer no guarantee against ad-hoc design or sloppy implementation, problems of the type mentioned above are less likely to go unnoticed when dealing with a system whose domain-specific information is supplied at run-time, especially when that information is being provided by the actual users of the system.</Paragraph>
    <Paragraph position="3"> By way of overview, we note that the TELI system derives from previous work on the LDC project, as documented in Ballard (1982), Ballard (1984), Ballard, Lusth and Tinkham (1984). and Ballard and Tinkham (1984). The initial prototype of TELI. which runs on a Symbolics Lisp Machine, is designed to answer English questions about information stored in one or more tables, (i.e. firstnormal-form relational database). A sample view of the display screen during a session with TELl. which may give the flavor of how the system operates, is shown in Figure L Information on some aspects of knowledge acquisition not discussed in this paper.</Paragraph>
    <Paragraph position="4"> particularly with regard to syntactic case frames, can be found in Ballard (1986).</Paragraph>
    <Paragraph position="5"> 2. Types of Modifiers Available in TELI The syntactic and semantic models adopted for TEL1 are intended to provide a unified treatment of a broad and extendible class of word and phrase types.</Paragraph>
    <Paragraph position="6"> By providing for an &amp;quot;extendible&amp;quot; class of constructs, we make the knowledge acquisition module of TELl independent of the natural language portion of the system, whose earlier version has been described in Ballard and Tinkham (1984) and Ballard. Lusth. and  Tinkham (1984), In the remainder of this paper, the reader should bear in mind that the acquisition modules of TEL1, including the menus they generate, are driven by extensible data structures that convey the linguistic coverage of the underlying natural language processor (NLP) for which information is being acquired. For example, incorporating adjective phrases into the system involved adding 12 lines of Lisp-like data specifications. This brevity is largely due to the use of case frames that embody dynamically alterable selectional restrictions (Ballard, 1986).</Paragraph>
    <Paragraph position="7"> As an initial feeling for the coverage of the NLP for which information is currently acquired, TEL1 provides semantics for the word categories Adjective e.g. an expensive restaurant Noun Modifier e.g. a graduate student Noun e.g. a pub and the phrase types Adjective Phrase e.g. employees responsible for the planning projects</Paragraph>
    <Section position="1" start_page="20" end_page="20" type="sub_section">
      <SectionTitle>
Noun-Modifier Phrase
</SectionTitle>
      <Paragraph position="0"> e.g. the speech researchers</Paragraph>
    </Section>
    <Section position="2" start_page="20" end_page="20" type="sub_section">
      <SectionTitle>
Prepositional Phrase
</SectionTitle>
      <Paragraph position="0"> e.g. the trails on the Franconia-Region map</Paragraph>
    </Section>
    <Section position="3" start_page="20" end_page="20" type="sub_section">
      <SectionTitle>
Verb Phrase
</SectionTitle>
      <Paragraph position="0"> e.g. employees that report to Brachman</Paragraph>
    </Section>
    <Section position="4" start_page="20" end_page="20" type="sub_section">
      <SectionTitle>
Functional Noun Phrase
</SectionTitle>
      <Paragraph position="0"> e.g. the size of department 11387, the colleagues of Litman In addition to these user-defined modifier types, the system currently provides for negation, comparative and superlative forms of adjectives, possessives, and ordinals. Among the grammatical features supported are passives for verbs, reduced relatives for prepositional and adjective phrases, fronting of verb phrase complements, and other minor features. One important area for expansion involves quantifiers.</Paragraph>
      <Paragraph position="1"> both logical (e.g. &amp;quot;all&amp;quot;) and numerical (e.g. &amp;quot;at least 3&amp;quot;).</Paragraph>
    </Section>
  </Section>
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